Basic Techniques Research Articles

O148: Unlocking Enhanced Immunity in Pancreatic Ductal Adenocarcinoma: Activins Interplay with CAF-Stroma Mechanisms

Abstract SMAD4 is a tumour suppressor gene that is mutated in up to 60% of pancreatic ductal adenocarcinoma (PDAC) tumours. Activins are members of the TGF-b signalling superfamily which signal through SMAD4 and are generally associated with an oncogenic process, with differing effects on tumour and stromal cells, such as cancer associated fibroblasts (CAFs). We sought to further elucidate the role of activin within PDAC and perturb activin signalling in vitro and in vivo. Analysis was performed of publicly available human datasets alongside human and murine single-cell RNA-sequencing datasets to study the effect of activin expression on survival and tumourigenesis. We developed anti-activin monoclonal antibodies to perturb activin signalling in PDAC mice, with deep analysis of tumour composition including immune cells and CAFs via a multitude of basic science techniques. We demonstrated that circulating activin levels are higher in PDAC patients than in healthy volunteers, whilst activin overexpression is associated with reduced overall survival in PDAC patients. Activin was shown to be predominantly expressed by contractile (collagen-depositing) CAFs, as opposed to inflammatory CAFs. Activin expression co-localises with fibroblasts, and anti-activin antibodies can reduce the collagen content of dense PDAC tumours. Additionally, anti-activin antibodies led to a statistically significant increase in CD4 and CD8 T-cell infiltration into murine PDAC tumours. We have shown that activin is overexpressed in PDAC, and high expression is associated with a more aggressive disease process. Anti-activin antibodies can alter the composition of desmoplastic PDAC tumours and increase the immune infiltrate of these typically “immune cold” tumours.

The Future of Material Scientists in an Age of Artificial Intelligence.

Material science has historically evolved in tandem with advancements in technologies for characterization, synthesis, and computation. Another type of technology to add to this mix is machine learning (ML) and artificial intelligence (AI). Now increasingly sophisticated AI-models are seen that can solve progressively harder problems across a variety of fields. From a material science perspective, it is indisputable that machine learning and artificial intelligence offer a potent toolkit with the potential to substantially accelerate research efforts in areas such as the development and discovery of new functional materials. Less clear is how to best harness this development, what new skill sets will be required, and how it may affect established research practices. In this paper, those question are explored with respect to increasingly more sophisticated ML/AI-approaches. To structure the discussion, a conceptual framework of an AI-ladder is introduced. This AI-ladder ranges from basic data-fitting techniques to more advanced functionalities such as semi-autonomous experimentation, experimental design, knowledge generation, hypothesis formulation, and the orchestration of specialized AI modules as stepping-stones toward general artificial intelligence. This ladder metaphor provides a hierarchical framework for contemplating the opportunities, challenges, and evolving skill sets required to stay competitive in the age of artificial intelligence.

Competitive Strategies and Performance of Kenya Airways Limited in Nairobi County, Kenya

Kenya Airways has experienced significant financial losses over a prolonged period, which has led to the requirement of a government bailout and the adoption of a restructuring initiative. Kenya Airways is a major player in the Kenyan aviation sector but has struggled to stay profitable compared to Ethiopian Airlines. Ethiopian Airlines has reported consistent profits for several years, in contrast. Kenya Airways is adopting competitive tactics to improve its performance, but there is a dearth of empirical research on the subject. The objective of this study was to analyse the impact of competitive strategies on the performance of Kenya Airways. The purpose of the study was to examine the impact of differentiation, cost leadership, focus, and innovation on the performance of Kenya Airways Limited. This study was anchored on the following theories: porter’s generic strategies model, dynamic capabilities, resource-based view, strategy-structure-performance, and balanced score card. This study employed a descriptive inquiry approach. The focus group for the study was comprised of a total of 180 staff members of Kenya Airways Limited. The sample size consisted of 124 employees, who were selected using a basic random sampling technique. A semi-structured questionnaire was used to collect primary data. This research assessed the accuracy of the research tool by utilizing the viewpoints of experts through a content validity method. Cronbach's alpha co-efficient was utilized to evaluate the dependability of the research instrument, and a minimum threshold of 0.7 was established. Data was analysed using descriptive statistics using means and standard deviations and inferential statistics. The study made use of correlation analysis and multiple regression analysis to deduce connections among different variables. Differentiation strategy had a positive and significant effect on performance of Kenya Airways of (β= 0.513, p < 0.05). Cost leadership strategy had a positive and significant effect on performance of Kenya Airways of (β=0.458, p < 0.05). Focus strategy had a positive and significant effect on performance of Kenya Airways of (β= 0.540, p < 0.05). Innovation strategy had a positive and significant effect on performance of Kenya Airways of (β=0.651, p < 0.05). The study concluded that differentiation strategy improves the performance of Kenya Airways. Cost leadership strategy helps to improve the performance of Kenya Airways Limited. Focus strategy enhances performance of Kenya Airways Limited and innovation strategy helps to improve performance of Kenya Airways Limited. The study recommended that the company should continue to offer unique features that sets it apart from other airlines. The company should operate efficiently in order to keep costs low.

Credit Card Fraud Detection using Machine Learning (Logistic Regression)

Abstract: Credit Card Fraud Detection (CCFD) is a crucial application in machine learning. It aims for safeguarding financial transaction. Identifying fraud transaction and real transactions and telling that is it fraud or real. Traditional methods for credit card fraud detection rely on basic statistical techniques .credit card remains a significant challenge in the financial industry .It rely on machine learning algorithms .Fraud detection very useful for financial institution and consumers worldwide .particularly logistic regression, has emerged as a potent tool in identifying fraudulent transactions. It will consider the before amount ,after amount ,time, pin numbers based on that it will detect fraud transactions .This paper explores the application of logistic regression in credit card fraud detection , focusing on its implementation ,challenges and effectiveness .This project works for finding fraud transactions. Logistic Regression ,have shown promising results in detecting fraudulent transactions.

Alginate beads loaded with rambutan extract: characterization and stability during in vitro gastrointestinal digestion.

Fallen young rambutan fruit is an underrated agricultural waste which may contain several bioactive compounds. In this study, fallen young rambutan fruit was assessed regarding its phenolic contents and antioxidant activities. In order to expand its utilization, rambutan extract-loaded hydrogel beads were developed by a basic spherification technique using sodium alginate. The effect of ratios of polymer and extract and different calcium sources were evaluated. The recovery of bioactive compounds from the hydrogel beads was determined using in vitro gastrointestinal digestion models. Use of 50% (v/v) ethanol yielded rambutan extract with good chemical properties. The production of hydrogel beads using a ratio of 1:3 with calcium lactate provided the highest production yield of 122.94%. The hydrogel beads developed using the ratio of 1:3 with a combination of calcium lactate and calcium chloride showed high recovery of phenolic compounds and antioxidant activity after simulated intestinal digestion, which were greater compared to unencapsulated extract. The findings demonstrate that the ratio of wall material to rambutan extract and the calcium source influence the physical properties, chemical properties and in vitro gastrointestinal digestion stability of alginate beads. The obtained hydrogel beads may have potential for application in the food or pharmaceutical industries. © 2024 Society of Chemical Industry.

Nucleic-Acid-Based Molecular Fungal Diagnostics: A Way to a Better Future.

The world has seen a tremendous increase in the number of fungal infections during the past two decades. Recently, the World Health Organisation released the pathogen priority list for fungal infections, signifying the importance of these infections in the fields of research and public health. Microbiology laboratories demand an upgrade in the diagnostic system to keep up with the increased burden of these infections. Diagnosis of fungal infections using conventional techniques has always faced limitations in terms of specificity, sensitivity, and turnaround time. Although these methods are the core pillars of the diagnosis, there is an increased need for molecular approaches. Molecular techniques have revolutionised the field of fungal diagnostics. The diverse array of molecular techniques, including techniques like Polymerase Chain Reaction (PCR), have emerged as a cornerstone in fungal diagnostics. Molecular techniques have transformed fungal diagnostics, providing powerful tools for the rapid and accurate identification of pathogens. As these technologies continue to evolve, their integration into routine clinical practice holds the promise of improving patient outcomes through timely and targeted antifungal interventions. This review will cover the molecular approaches involved in fungal diagnostics, moving from the basic techniques to the advanced-level nucleic-acid-based molecular approaches providing a high throughput and decreased turnaround time for the diagnosis of serious fungal infections.

Robotic-Assisted DIEP Flap Harvest for Autologous Breast Reconstruction: Case Report, Technical Aspects and Identification of Suitable Patients

Robotic-assisted harvest of the deep inferior epigastric perforator (DIEP) flap is an innovative modification of the traditional open preparation for autologous breast reconstruction. It is assumed that donor-site morbidity (herniae, bulging) is reduced by minimising the fascial incision length in robotic-assisted DIEP flap harvest. This is the first report of a robotic-assisted DIEP harvest in Germany, which was performed in April 2023 at the University Hospital of Freiburg in an interdisciplinary approach of the Departments of Plastic Surgery, Urology and Gynaecology. To determine the value of this novel technique, we assessed the demand by retrospectively performing an analysis of potential patients and conducted a cost analysis based on the breast reconstructions with DIEP flap harvest performed between April 2021 and May 2023 at the Department of Plastic Surgery at Freiburg University Hospital. To this end, we carried out a retrospective analysis of preoperative CT angiographies to determine the proportion of patients suitable for a robotic-assisted procedure in a post-hoc analysis. Furthermore, we describe the basic robotic-assisted techniques and discuss the TEP and TAPP laparoscopic approaches. In line with the previously published literature, a short intramuscular course (≤25 mm) and a perforator diameter of≥1.5 mm and≥2.7 mm (subgroup) were defined as a crucial condition for the robotic-assisted procedure. We analysed 65 DIEP flaps harvested in 51 patients, of which 26 DIEP flaps in 22 patients met both criteria, i. e.≤25 mm intramuscular course and≥1.5 mm diameter of the perforator, while 10 DIEP flaps in 10 patients additionally met the criteria of the subgroup (≥2.7 mm diameter). Based on the intramuscular course of the perforators in the CT angiographies of those 26 DIEP flaps, a potential reduction of the fascial incision of 96.8±25.21 mm (mean±standard deviation) compared with the conventional surgical approach was calculated. The additional material costs in our case were EUR 986.01. However, ischaemia time was 33,5 minutes longer than the median of the comparative cohort. The robotic-assisted procedure has already proven to be a feasible alternative in a suitable patient population. However, further studies are needed to confirm that robotic-assisted DIEP flap harvest actually reduces harvest site morbidity and thereby justifies the additional costs and complexity.

Aorta Segmentation in 3D CT Images by Combining Image Processing and Machine Learning Techniques.

Aorta segmentation is extremely useful in clinical practice, allowing the diagnosis of numerous pathologies, such as dissections, aneurysms and occlusive disease. In such cases, image segmentation is prerequisite for applying diagnostic algorithms, which in turn allow the prediction of possible complications and enable risk assessment, which is crucial in saving lives. The aim of this paper is to present a novel fully automatic 3D segmentation method, which combines basic image processing techniques and more advanced machine learning algorithms, for detecting and modelling the aorta in 3D CT imaging data. An initial intensity threshold-based segmentation procedure is followed by a classification-based segmentation approach, based on a Markov Random Field network. The result of the proposed two-stage segmentation process is modelled and visualized. The proposed methodology was applied to 16 3D CT data sets and the extracted aortic segments were reconstructed as 3D models. The performance of segmentation was evaluated both qualitatively and quantitatively against other commonly used segmentation techniques, in terms of the accuracy achieved, compared to the actual aorta, which was defined manually by experts. The proposed methodology achieved superior segmentation performance, compared to all compared segmentation techniques, in terms of the accuracy of the extracted 3D aortic model. Therefore, the proposed segmentation scheme could be used in clinical practice, such as in treatment planning and assessment, as it can speed up the evaluation of the medical imaging data, which is commonly a lengthy and tedious process.

Transform Domain-Based Perceptual Detection and Reduction of Blocking Artifacts

In this paper, provide a simple and effective method for measuring blocking artefacts with an ideal 2-D step function in this study. First, a basic edge detection technique for measuring blocking artefacts is proposed. The ideal 2-D step function is chosen based on the presence of blocking artefacts in the edge image. The blocking artefact reduction algorithm in frequency domain is designed to extract all of the parameters required to detect the presence of blocking artefacts and replace the optimal step function with a ramp function by replacing the coefficient of the first row of horizontal blocks with the coefficient of the shifted block. The proposed strategy was tested on various standard benchmark photos and found to increase the perceptual quality of JPEG compressed images after blocking artefact removal with the proposed method.

Correlational Analysis: Knowledge, Training, and Attitude Towards First Aid Injuries Among Students of Astate Senior High School in Banjarmasin

ABSTRACT Childhood injury is a growing public health concern that requires special attention. Students frequently participate in activities without considering the influence on their own body, resulting in injuries that can have a negative impact on their health and daily activities. The goal of this study was to assess the association between students' knowledge, training, and attitude toward first aid for injuries in a state senior high school in Banjarmasin. A correlational study design and a cross-sectional approach were utilized in this investigation. Data was obtained from a total of 1280 respondents, and a sample of 114 respondents was analyzed using a basic random sampling technique with probability sampling, with Spearman's rho as the statistical test utilized. With a p value of 0.05, the results suggest that there is a relationship between the level of knowledge, training, and attitude and the level of accuracy in first aid. It can be concluded that understudies' knowledge, training, and state of mind influence the precision of giving first aid for injuries, so it is critical for understudies to have positive knowledge, preparation, and demeanor in giving first aid to avoid mistakes that can lead to crises. Keywords: Attitude, First Aid for Injuries, Level of Knowledge, Training

Pengembangan bisnis jasa “kaluna badminton club” menggunakan business model canvas

Pengembangan bisnis jasa “kaluna badminton club” menggunakan business model canvas

SURVEI KEMAMPUAN SERVIS DALAM PERMAINAN BOLA VOLI KLUB TANGGO RAJO

Abstract
 
 This research was motivated by not knowing whether the service technique used was correct or not, and not knowing the player's level of ability regarding basic volleyball techniques. This study aims to determine the level of upper serve and lower serve abilities of volleyball players at the Tanggo Rajo club, Kab. Tebo. This research uses quantitative descriptive methods. The population is all volleyball players at the Tanggo Rajo club, Kab. Tebo, numbering 15 people. The sampling technique used total sampling with a research sample of 15 players. Data collection techniques using tests. The instrument used is the American Association for Health, Physical Education, and Recreation (AAHPER) serving accuracy test. The analysis technique used is to put the frequency into percentage form. The results of this research indicate that the level of service ability of volleyball players at Tanggo Rajo Club, Kab. Tebo is sufficient considering the highest frequency, namely the sufficient category with 7 people, namely 47%. Level of service ability of Tanggo Rajo Club volleyball players, Kab. Tebo was categorized as very good at 13%, good at 13%, fair at 47%, poor at 20%, very poor at 7%. Meanwhile, the lower level of service ability of the Tanggo Rajo Club volleyball players, Kab. Tebo is sufficient considering the highest frequency, namely the sufficient category with 6 people, namely 40%. Level of lower service ability of Tanggo Rajo Club volleyball players, Kab. Tebo was categorized as very good at 7%, good at 20%, fair at 40%, poor at 33%, very poor at 0%..
 Keywords : Ability, Upper Serve, Lower Serve

A survey of millimeter wave backscatter communication systems

Backscatter communication is an emerging low-power communication technology that has been integrated into the Internet of Things (IoT) due to its exceptional self-sustainability. However, conventional backscatter communication (BackCom) technologies often encounter limitations in data transmission rates, making it challenging to meet the growing bandwidth demands of IoT applications. In contrast, millimeter wave (mmWave) BackCom exhibits significant potential for high-speed data transmission owing to its abundant spectrum resources. Therefore, this paper presents a comprehensive survey of the existing literature on mmWave BackCom. We start by introducing the fundamental principles of mmWave BackCom, encompassing its architecture, basic techniques, and foundational knowledge. Subsequently, we review various mmWave backscatter communication techniques proposed in the current literature. Finally, we discuss several applications based on these techniques before finally addressing challenges and open issues associated with mmWave backscatter.

Pengembangan Instrumen Pengukuran Keterampilan Dasar Bermain Futsal Pada Siswa Sekolah Dasar

The purpose of this study was to develop types of futsal basic skill instruments that have certain characteristics according to the actual game of futsal, so that it fullfil validity and reliability requirement to measure playing futsal basic technique skill properly. The type of research applied is development research. The subjects of this study were elementary school students who took part in futsal extracurricular activities aged 10 to 12 years who took part in regular competitions at their schools, both at the sub-district and city levels. The research findings based on data analysis are the type of skill test for baiting the ball with a distance of 2.5 meters which has a validity value of 0.561 and a reliability of 0.90, the type of skill test holding the ball for a duration of 30 seconds which has a validity value of 0.732 and a reliability of 0.830, the type the skill test of kicking the ball to the target has a validity value of 0.717 and a reliability of 0.778, and the type of dribbling skill test has a validity value of 0.838 and a reliability of 0.956. The conclusion in the basic skills of playing futsal that are most dominant are the type of instrument passing (passing) with a percentage of 35.35%, holding the ball (controlling) with a percentage of 28.5%, shooting with a percentage of 19.35%, and dribbling (dribbling) with a percentage of 16.65%.

NEW EXTRACTION METHOD OF ENTOMOPATHOGENIC NEMATODES USING THE BASIC FLOTAC AND THE MINI-FLOTAC TECHNIQUES

The FLOTAC basic technique is a recognised method used mainly in the veterinary field to extract parasites from the faeces of animals found in the stomach and intestine. This study is the first application of the FLOTAC and Mini-FLOTAC techniques to extract infective juveniles of entomopathogenic nematodes from infested Galleria mellonella. The EPN used for this purpose was an endemic Italian nematode belonging to the Rhabitidae family Steinernema carpocapsae. Galleria mellonella larvae were infected and extraction was performed a few days after infection using both techniques. A comparison was then made between the two methods. The results showed that infective juveniles could be extracted from the infected larva as early as three days after infection. The difference between the FLOTAC basic technique and the Mini-FLOTAC technique was not significant in the extraction of entomopathogenic nematodes. Due to its sensitivity and operating easiness the Mini-FLOTAC technique is a promising method for the extraction of entomopathogenic nematodes. It allows faster extraction of nematodes from the inhabited soil and insect host than the conventional White trap method. Key Words: Microbial biocontrol, Entomopathogenic nematodes, Nematode extraction, FLOTAC, Mini-FLOTAC

Korfball Coach Training in Klaten Regency, Central Java

The community service activity for training korfball coaches in Klaten Regency, Central Java aims to provide an understanding of training methods and an understanding of preparing training programs so that coaches can form and produce korfball athletes who excel in regional, national and even international championships. The method applied used a socialization approach with a training program followed by 50 participants consisting of teachers and football coaches in Central Java. The activity was held at KONI Klaten Regency for two days. The materials used in this activity are power points, teaching materials and videos as well as using laptops, projectors, mics and sound, stationery, documentation tools, korf and koftball balls. The first socialization material explains basic techniques, methods of training koftball and rules for playing koftball games. The second material discusses guidelines for preparing a simple exercise program. The third material discusses the importance of physiotherapy in the sport of korfball. Then the fourth material concerns physical training methods, techniques and tactics in korfball. The final material is about sports management in improving performance. After delivering all the material, it was continued with a korfball game simulation. The output of this activity is improving the quality of human resources for korfball coaches in Central Java.

Time-predictable task-to-thread mapping in multi-core processors

The performance of time-predictable systems can be improved in multi-core processors using parallel programming models (e.g., OpenMP). However, schedulability analysis of parallel applications is a big challenge due to their sophisticated structure. The common drawbacks of current task-to-thread mapping approaches in OpenMP are that they (i) utilize a global queue in the mapping process, which may increase contention, (ii) do not apply heuristic techniques, which may reduce the predictability and performance of the system, and (iii) use basic analytical techniques, which may cause notable pessimism in the temporal conditions. Accordingly, this paper proposes a task-to-thread mapping method in multi-core processors based on the OpenMP framework. The mapping process is carried out through two phases: allocation and dispatching. Each thread has an allocation queue in order to minimize contention, and the allocation and dispatching processes are performed using several heuristic algorithms to enhance predictability. In the allocation phase, each task-part from the OpenMP DAG is allocated to one of the allocation queues, which includes both sibling and child task-parts. A suitable thread (i.e., allocation queue) is selected using one of the suggested heuristic allocation algorithms. In the dispatching phase, when a thread is idle, a task-part is selected from its allocation queue using one of the suggested heuristic dispatching algorithms and then dispatched to and executed by the thread. The performance of the proposed method is evaluated under different conditions (e.g., varying the number of tasks and the number of threads) in terms of application response time and overhead of the mapping process. The simulation results show that the proposed method surpasses the other methods, especially in the scenario that includes overhead of the mapping. In addition, a prototype implementation of the main heuristics is evaluated using two kernels from real-world applications, showing that the methods work better than LLVM's default scheduler in most of the configurations.

Unmanned aerial vehicle face recognition technology research progress

In recent years, face recognition technology has become a significant advance in the area of biometrics and machine vision. It paves the way for a wide range of applications, including security systems, access control, surveillance, and user authentication. These applications are undoubtedly a major innovation in the field of UAV, which will greatly expand and extend its application scenarios. This paper shows a compositive review of UAV facial identification technology, including its basic principles, techniques, challenges, and ethical considerations. According to the different stages, this paper focuses on RCNN and YOLO, two more widely used target detection technologies and their respective technical iterations, and through the comparison of the two in terms of technical characteristics and application scenarios, the advantages of the two are obtained, and combined with the current UAV workflow. Get the stage in which they play a specific role. This paper reviews the existing literature and research on face recognition, aiming to help people better understand the current process of this technology and its wider social application and impact.

A hyperspectral unmixing approach for ink mismatch detection in unbalanced clusters

Detecting ink mismatch is a significant challenge in verifying the authenticity of documents, especially when dealing with uneven ink distribution. Conventional imaging methods frequently fail to distinguish visually similar inks. Our study presents a novel hyperspectral unmixing approach to detect ink mismatches in unbalanced clusters. The proposed method identifies unique spectral characteristics of different inks employing k-means clustering and Gaussian mixture models (GMMs) to perform color segmentation on different ink types and utilizes elbow estimation and silhouette coefficient to evaluate the number of inks estimation precisely. For a more accurate estimation of quantity, which is generally not an attribute of clustering methods, we employed entropy calculations in the red, green, and blue depth channels for precise abundance estimation of ink. This unique combination of basic techniques in conjunction exhibits better efficacy in performing ink unmixing and provides a real-world document forensic solution compared to current methods that rely on assumptions like prior knowledge of the inks used in a document and deep learning-based methods that rely heavily on abundant training datasets. We evaluate our approach on the iVision handwritten hyperspectral images dataset (iVision HHID), which is a comprehensive and rich dataset that surpasses the commonly-used UWA writing inks hyperspectral images (WIHSI) database in size and diversity. This study has accomplished the unmixing task with three main challenges: unmixing of diverse ink spectral signatures (149 spectral bands instead of 33 bands in the previous dataset), without using prior knowledge and assumptions about the number of inks used in the questioned document, and not requiring large training data for performing unmixing. Furthermore, the security of the proposed document authentication methodology to address the likelihood of forgeries or manipulations in questioned documents is enhanced as compared to previous works relying on known inks and known spectrum. Randomization techniques and anomaly detection mechanisms are used in our methodology which increases the difficulty for adversaries to predict and manipulate specific aspects of the input data in questioned documents, thereby enhancing the robustness of our method. The code for conducting this research can be accessed at GitHub repository.

Standardized Pre-clinical Surgical Animal Model Protocol to Investigate the Cellular and Molecular Mechanisms of Ischemic Flap Healing

BackgroundSome of the most complex surgical interventions to treat trauma and cancer include the use of locoregional pedicled and free autologous tissue transfer flaps. While the techniques used for these reconstructive surgery procedures have improved over time, flap complications and even failure remain a significant clinical challenge. Animal models are useful in studying the pathophysiology of ischemic flaps, but when repeatability is a primary focus of a study, conventional in-vivo designs, where one randomized subset of animals serves as a treatment group while a second subset serves as a control, are at a disadvantage instigated by greater subject-to-subject variability. Our goal was to provide a step-by-step methodological protocol for creating an alternative standardized, more economical, and transferable pre-clinical animal research model of excisional full-thickness wound healing following a simulated autologous tissue transfer which includes the primary ischemia, reperfusion, and secondary ischemia events with the latter mimicking flap salvage procedure.ResultsUnlike in the most frequently used classical unilateral McFarlane’s caudally based dorsal random pattern skin flap model, in the herein described bilateral epigastric fasciocutaneous advancement flap (BEFAF) model, one flap heals under normal and a contralateral flap—under perturbed conditions or both flaps heal under conditions that vary by one within-subjects factor. We discuss the advantages and limitations of the proposed experimental approach and, as a part of model validation, provide the examples of its use in laboratory rat (Rattus norvegicus) axial pattern flap healing studies. ConclusionsThis technically challenging but feasible reconstructive surgery model eliminates inter-subject variability, while concomitantly minimizing the number of animals needed to achieve adequate statistical power. BEFAFs may be used to investigate the spatiotemporal cellular and molecular responses to complex tissue injury, interventions simulating clinically relevant flap complications (e.g., vascular thrombosis) as well as prophylactic, therapeutic or surgical treatment (e.g., flap delay) strategies in the presence or absence of confounding risk factors (e.g., substance abuse, irradiation, diabetes) or favorable wound-healing promoting activities (e.g., exercise). Detailed visual instructions in BEFAF protocol may serve as an aid for teaching medical or academic researchers basic vascular microsurgery techniques that focus on precision, tremor management and magnification.Graphical